Device, system and method for perioperative pain management

Inventors

Zuckerman-Stark, Galit • Costa, Adi

Assignees

Medasense Biometrics Ltd

Abstract

Method, device, system and associated processing logic for providing optimal perioperative nociception management to anesthetized patient, including monitoring a plurality of nociception-related physiological parameters of the patient using at least two non-invasive physiological sensors; combining the plurality of nociception-related physiological parameters into a nociception index value indicative of a level of nociception of the patient, by applying a machine learning algorithm on the plurality of nociception-related physiological parameters and/or features derived therefrom; comparing the nociception index value to a first threshold value indicative of an upper limit of nociceptive-anti-nociceptive balance (NANB) and to a second threshold value indicative of a lower limit of NANB; and providing a treatment or treatment recommendation based on the comparison and on a clinical concern.

Core Innovation

The invention provides a perioperative nociception-management system for an anesthetized patient that computes a nociception index value indicative of a level of nociception. A processing unit receives a plurality of nociception-related physiological parameters from at least one physiological sensor of a first monitoring unit and receives, from an external monitor, an indication regarding a physiological signal related to a clinical concern. The processing unit applies a machine learning algorithm to the plurality of nociception-related physiological parameters and/or features derived therefrom to compute the nociception index value.

The computed nociception index value is compared to predetermined threshold values and is evaluated using predetermined minimal amount of time conditions. When the nociception index value exceeds a predetermined threshold value for a predetermined minimal amount of time, the processing unit issues a recommendation to increase analgesic dosing or triggers an operational command affecting a medicament administration device to increase the analgesic dosing. When the nociception index value is below the upper threshold but above a predetermined lower threshold value, the processing unit issues a recommendation to administer an anti-hypertensive agent or a sympathomimetic/adrenergic drug, or triggers an operational command affecting the medicament administration device to administer the medicament.

The system further compares timing and dosing constraints to decide when to decrease analgesic dosing. When the nociception index value is below the lower threshold value for a predetermined minimal amount of time and the analgesic dosing is above a minimal dosing, the processing unit issues a recommendation to decrease analgesic dosing or triggers an operational command affecting the medicament administration device to decrease the analgesic dosing. In another embodiment, the system uses clinical concern indications including mean arterial blood pressure at or below a predetermined lower threshold value, a decrease in mean arterial blood pressure relative to a baseline mean arterial blood pressure of about 15% or more, and/or heart rate at or below a predetermined low threshold value, and uses additional decisions based on determining a hypovolemia value and issuing recommendations to increase rate of fluids or adjust analgesic dosing.

Claims Coverage

The partial content includes two independent claims (device claims) that share a common inventive structure: sensing nociception-related physiological parameters, computing a machine-learning nociception index (NOL), and using threshold and minimal-time conditions to drive medication-related recommendations or operational commands. The independent claims further differ in how the clinical concern is expressed and how the treatment branch includes either anti-hypertensive or sympathomimetic/adrenergic adjustment, or hypovolemia/fluid-rate determination and analgesic adjustment.

Across the independent claims, the core coverage is a device that computes a machine-learning nociception index from nociception-related physiological parameters and then applies NOL threshold comparisons with predetermined minimal-time conditions to issue recommendations or operational commands that adjust analgesic dosing and administer different classes of medicaments based on intermediate versus extreme NOL values, while incorporating clinical concern input expressed using MAP and HR threshold criteria. One independent claim additionally uses a hypovolemia value decision to branch to a fluids-rate recommendation or an analgesic increase recommendation.

Stated Advantages

Documented Applications

No documented applications found